IEEE International Conference on Computer Vision (ICCV 2015), Workshop on Inverse Rendering, 2015, Note: This work has been presented as a poster and is not included in the workshop proceedings. (poster)

2012

Patient motion in the scanner is one of the most challenging problems in MRI. We propose a new retrospective motion correction method for which no tracking devices or specialized sequences are required. We seek the motion parameters such that the image gradients in the spatial domain become sparse. We then use these parameters to invert the motion and recover the sharp image. In our experiments we acquired 2D TSE images and 3D FLASH/MPRAGE volumes of the human head. Major quality improvements are possible in the 2D case and substantial improvements in the 3D case.

Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems